Apache Airflow
Programmatically author, schedule, and monitor workflows.
Apache Airflow® is a community-driven platform for programmatically authoring, scheduling, and monitoring workflows. It features a modular architecture, dynamic pipeline generation using Python, and a robust web application for workflow management.
Apache Airflow® is a platform created by the community to programmatically author, schedule, and monitor workflows. It features a modular architecture and utilizes a message queue to orchestrate an arbitrary number of workers, making it ready to scale to infinity.
Key features of Apache Airflow® include the ability to define pipelines in Python, allowing for dynamic pipeline generation, and the option to easily define custom operators to fit specific environments. The core of Airflow is built around parametrization, utilizing the powerful Jinja templating engine, which enhances flexibility in workflow creation.
Targeted at anyone with Python knowledge, Apache Airflow® enables users to deploy workflows for various applications, including building ML models, transferring data, and managing infrastructure. The platform offers a robust and modern web application for monitoring, scheduling, and managing workflows, eliminating the need for outdated command-line interfaces.
With many plug-and-play operators available for integration with services like Google Cloud Platform, Amazon Web Services, and Microsoft Azure, Apache Airflow® is designed to seamlessly fit into existing infrastructures and adapt to next-gen technologies, providing significant benefits in workflow management and execution.
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Pricing Plans
Pricing Model: free (open source)
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